We propose a methodology to classify individuals into few but meaningful health groups by estimating a panel Markov switching model that exploits rich information from panel household surveys. Using the HRS, we identify four persistent health groups, depending on individual's physical and mental disabilities. Our classification outperforms existing health measures at explaining entry in nursing homes, home health care, out-of-pocket medical expenses, and mortality for individuals in the HRS, ELSA, and SHARE. Through a workhorse model of savings, we recover an asset cost of bad health that is twice as big as when using self-reported health.

中文翻译：

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老年人的内生健康群体和异质动态

我们提出了一种方法，通过估计利用来自面板家庭调查的丰富信息的面板马尔可夫切换模型，将个人分为少数但有意义的健康群体。使用 HRS，我们根据个人的身体和精神残疾确定了四个持续健康组。我们的分类在解释 HRS、ELSA 和 SHARE 中个人进入疗养院、家庭保健、自付费用医疗费用和死亡率方面优于现有的健康指标。通过储蓄的主力模型，我们收回了健康状况不佳的资产成本，是使用自我报告健康状况时的两倍。